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cs.CL2026
GroundAct: Can LLM Agents Ground Actions in Environmental States?
Zixuan Wang, Dingming Li, Hongxing Li +8
LLM agents achieve 85-96% success on tasks where instructions fully specify the action, but drop to 29-53% when action feasibility depends on environmental state that the instructi…
cs.CL2026
Milestone-Guided Policy Learning for Long-Horizon Language Agents
Zixuan Wang, Yuchen Yan, Hongxing Li +7
While long-horizon agentic tasks require language agents to perform dozens of sequential decisions, training such agents with reinforcement learning remains challenging. We identif…